Design and build Spark data ETL pipelines on AWS data platform
Collaborate with cross functional teams (data scientists, fraud, marketing) to understand data needs and deliver solutions
Optimize data infrastructure
Ensure data quality and reliability
Innovate and follow best practices
Ensure operational excellence of the data platform

Requirements

Professional experience working in data warehousing, data architecture, and/or data engineering environments
Proficiency in at least one high-level programming language (Scala, Java, Python or equivalent)
Good understanding of databases
Built large-scale data products
Deep understanding of system design, data structures, and algorithms
Excellent knowledge of distributed computing frameworks such as Hadoop MapReduce, Spark
Strong knowledge of following AWS infrastructure - EMR, S3, Lambda, Redshift etc
Strong understanding of data quality, governance
Team player, self-driven, highly motivated individual who loves to learn new things.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SparkETLdata warehousingdata architecturedata engineeringScalaJavaPythonHadoop MapReducedata structures

Soft Skills

collaborationdata qualityoperational excellenceself-drivenhighly motivatedteam playerinnovationbest practicescommunicationproblem-solving